Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/oldskultxo/aictx/agents-mdgit clone --depth 1 https://github.com/oldskultxo/aictxWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/oldskultxo/aictx/agents-md)<a href="https://agentmods.dev/instructions/oldskultxo/aictx/agents-md"><img src="https://agentmods.dev/badge/instructions/oldskultxo/aictx/agents-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01292 | $0.01292 |
| Opus 5 | $0.00646 | $0.00646 |
| Sonnet 5 | $0.00258 | $0.00258 |
| Haiku 4.5 | $0.00129 | $0.00129 |
Grade A, and why
aictx AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS Instructions for aictx
aictxis the distributable multi-LLM installer/runtime layer for.aictx_*.- Local filesystem artifacts are created by scripting/runtime, never by the LLM.
- Prefer eager scaffold semantics: structure exists immediately after
aictx init. - Cross-project behavior must come from workspace registry/config, never hardcoded machine paths.
- For subsystem changes, validate with
python3 -m aictx internal migrate,internal boot,internal query,internal packet,internal memory-graph --refresh, andreport real-usage --repo <repo>when relevant.
AI Context Engine
This repository is initialized for aictx.
Agent rules:
- Enter the runtime middleware for every execution in initialized repos.
- The AICTX lifecycle remains
prepare/startup context → resume capsule → work → finalize → final AICTX summary/persistence. - MCP-first startup:
- If AICTX MCP tools are already visible, use MCP tools for resume/finalize.
- If AICTX MCP tools are not visible but
.mcp.jsonor.vscode/mcp.jsonexists, first use runner tool discovery when available (for example search foraictx resume finalize lifecycle) so lazy-loaded MCP namespaces can attach, then have the runner attach/start the configured stdio MCP server before the first AICTX command of each new session. - If MCP tools still are not attached after discovery/attachment, state that MCP config exists but tools are unavailable in this runner and use the CLI fallback.
- At session start:
- Extract the task goal from the user prompt.
- Run exactly one AICTX continuity command: MCP resume when available, otherwise
aictx resume --repo . --task "<task goal>" --json. - Do not pass the full user prompt to resume; exclude reporting instructions, metrics schemas, output format rules, final answer format, benchmark/evaluation harness text, logging instructions, and meta-instructions about how to report the work.
- After task work, run exactly one AICTX finalization command: MCP finalize when available, otherwise
aictx finalize --repo . --status success|failure --summary "<what happened>" --json. - Use the returned continuity capsule as the operational brief during normal agent startup; follow
execution_contract.first_actionbefore repo-wide orientation, edit withinexecution_contract.edit_scope, runexecution_contract.test_command.command, then finalize. - Render exactly one startup banner source: normal agent startup uses
resume.startup_banner_textorresume.startup_banner_render_payload; wrapped execution usesprepare_execution().startup_banner_textorprepare_execution().startup_banner_render_payload. Do not render both. resumeis the canonical agent-facing continuity query; it does not replaceprepare_execution,aictx finalize, the startup banner, the final AICTX summary, or persistence.- Do not inspect
.aictx/. - Do not run exploratory AICTX commands.
- Do not run
aictx internal,aictx -h,aictx reuse,aictx suggest,aictx next,aictx task,aictx messages,aictx reflect, oraictx reportduring normal task startup unless the user asks for AICTX diagnostics, the task is about AICTX itself, resume is missing/corrupt/contradictory, or finalization/update lifecycle requires it. - On the first execution of each visible session, always show the startup banner at the start of the first substantive user-visible response; do not consume it with a transient progress/status message that will be omitted from the final task response. Render the selected resume/prepare startup banner in the current user language. When the selected startup banner policy points to a structured render payload, prefer that structured payload for localization and use compact text only as the fallback source. You may fully rephrase human-readable prose from structured factual fields while preserving exact facts, file paths, commands, flags, package names, test names, code identifiers, and other technical tokens; do not add, remove, reorder, reinterpret, or invent facts. If first-session text is missing, render
{agent_label} · session #{session_count} · awakefrom selected identity fields. Do not render it again afteralready_shownis true. - Use
aictx finalize --repo . --status success|failure --summary "<what happened>" --jsonfor normal agent finalization. finalize_execution is the middleware API behind that command; do not call it directly from the shell. Do not runaictx internal execution finalizeduring normal task flow. - After finalize, append the AICTX final summary to the final user response, using
agent_summary_textas the compact fallback user-facing source. Whenagent_summary_policy.render_payload_fieldpoints toagent_summary_render_payload, prefer that structured payload for localization while preserving exact facts, technical tokens, and the details/continuity link targets. Render every provided summary section, includingdetails,continuity_view_file, andcontinuity_view_online; do not replace Mermaid URLs with placeholders and do not manually reconstruct or retype pako URLs. - If no finalize output exists, say
AICTX summary unavailable. - Use the
aictx resumecapsule before deeper repo analysis. .aictx/memory/source/is editable source knowledge; do not hand-edit generated derived artifacts under.aictx/boot,.aictx/store,.aictx/indexes,.aictx/metrics, and similar runtime folders.- Use
resume.runtime_text_policy/resume.communication_policy,prepared.runtime_text_policy,prepared.startup_banner_policy, andfinalized.agent_summary_policywhen available. - You may enrich AICTX-originated user-visible texts if helpful, but you must preserve real facts and never invent missing data.
- Advanced/diagnostic/building-block commands remain available for humans and diagnostics, but normal agents should not use them during startup.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 45 lines · 1,292 tokens per session scan A 099727d0114a
aictx AGENTS.md is an instructions file published in the GitHub repository oldskultxo/aictx (57 stars, last pushed 2mo ago), licensed MIT. It adds 1,292 tokens to every session, about $0.0065 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
ContextLattice AGENTS.md
Instructions for sheawinkler/ContextLattice, covering agent instructions, start, work loop, hooks and host lifecycle safety.
agent-memory-kit CLAUDE.md
Claude Code instructions for awrshift/agent-memory-kit, covering working on memory kit, rules that are easy to get wrong, before committing a change to hooks or skills, docs that must stay true in the same commit and language.
memory-journal-mcp copilot-instructions.md
Copilot instructions for neverinfamous/memory-journal-mcp, covering memory journal mcp — copilot code review context, project overview, session context, tooling standards and coding standards.
structured-context-spec CLAUDE.md
Instructions for tim-mccrimmon/structured-context-spec, covering claude.md, structured context specification (scs) — project context, what this project is, repository structure and tools & development commands.
engineering-os AGENTS.md
AGENTS.md instructions for engineering-os/engineering-os, covering @engineering-os/monorepo — engineering os managed, mandatory eos mcp usage, rules, codex review guidelines and eos codex skills.
copilot-memory-store copilot-instructions.md
Instructions for timothywarner-org/copilot-memory-store, covering copilot memory store – ai agent instructions, core modules, memory file behavior, cli & mcp workflows and llm compression.